Take a Chance on Me: Aleatory Poetry, Generative AI, and the External Demarcation Problem

• Published in: The Journal of aesthetics and art criticism Vol. 81; no. 4; pp. 508 - 524
• Main Author: Chen, Melvin
• Format: Journal Article
• Language: English
• Published: UK Oxford University Press 31.12.2023
• Subjects: Aesthetics; Conceptual analysis; Generative artificial intelligence; Hypotheses; Poetry; Visual arts
• ISSN: 0021-8529; 1540-6245
• DOI: 10.1093/jaac/kpad042

Abstract What is it in virtue of which any poetic output will be included or excluded from the category of art? I will first identify the external demarcation problem, which is concerned with whether or how the cut-off is made between art and non-art. I will then adopt a nonclassical approach to conceptual analysis by relying on a set of examples of poetry generated by aleatory processes to evaluate an intention-based response to the external demarcation problem. I will argue in favor of an intention-based response that is grounded in hypothetical intentionalism. According to this response, a contextually informed audience will form a hypothesis about poetic intentions on the basis of the evidence that a work makes publicly available. Semantic, categorial, and ostensive intention and intention traces may help this audience to determine whether a work counts as art and is worth effortful interpretation. My proposed version of an intention-based response to the external demarcation problem will be based on the p-valued hypothesis-testing approach in science and will be highly relevant to a context of production in which we find human poets, poetry-generating AI systems, and human-AI interfaces.